CN111191556A - Face recognition method and device and electronic equipment - Google Patents
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Abstract
The embodiment of the disclosure provides a face recognition method, a face recognition device and electronic equipment, and belongs to the technical field of image processing. The face recognition method comprises the following steps: the scheme comprises the following steps: collecting image information of a preset area; detecting whether a moving object appears in the preset area or not by using a movement detection algorithm according to the image information; if the mobile object is detected to appear in the preset area, identifying whether the face exists in the preset area or not; and if the human face exists in the preset area, acquiring a human face image of the preset area. Through the scheme disclosed by the invention, the passing speed of the user using the face recognition terminal equipment can be effectively increased or the snapshot rate of the face snapshot equipment can be increased.
Description
Technical Field
The present disclosure relates to the field of image processing technologies, and in particular, to a face recognition method and apparatus, and an electronic device.
Background
At present, a face recognition terminal device wakes up a screen after detecting a face through a face detection algorithm, and then performs subsequent tasks of face key point detection, face tracking, living body recognition and face recognition. The face snapshot device also detects a face through a detection algorithm at any moment, and then conducts face snapshot through a face tracking algorithm, a face quality judgment algorithm and the like. However, face detection algorithms typically have an acceptable minimum detected face and a maximum detected face. Therefore, when the user does not know or cannot judge the usable range of the face recognition terminal equipment, poor user experience can be brought; in addition, the face detection algorithm is relatively time consuming, which may increase the user's waiting time or miss capturing many faces.
Therefore, the prior face recognition scheme has the technical problems of overlong waiting time or more missing recognition times.
Disclosure of Invention
In view of this, embodiments of the present disclosure provide a face recognition method, a face recognition apparatus, and an electronic device, which at least partially solve the problems in the prior art.
In a first aspect, an embodiment of the present disclosure provides a face recognition method, including:
collecting image information of a preset area;
detecting whether a moving object appears in the preset area or not by using a movement detection algorithm according to the image information;
if the mobile object is detected to appear in the preset area, identifying whether the face exists in the preset area or not;
and if the human face exists in the preset area, acquiring a human face image of the preset area.
According to a specific implementation manner of the embodiment of the present disclosure, the step of detecting whether a moving object appears in the preset area by using a motion detection algorithm according to the image information includes:
acquiring a background image of the preset area;
extracting a background image of the preset area from the image information of the preset area by using a background extraction algorithm to obtain a foreground image of the preset area;
and judging whether the preset area has a moving object or not according to the foreground image of the preset area.
According to a specific implementation manner of the embodiment of the present disclosure, the background extraction algorithm includes: background subtraction method, ViBe algorithm or ViBe + algorithm.
According to a specific implementation manner of the embodiment of the disclosure, the image information of the preset region comprises continuous multi-frame real-time images, and the background extraction algorithm is a background subtraction method;
the step of obtaining the background image of the preset area includes:
taking a first frame image in the continuous multi-frame real-time images as a background image of the preset area;
the step of extracting the background image of the preset area from the image information of the preset area by using a background extraction algorithm to obtain the foreground image of the preset area comprises the following steps:
and carrying out difference operation on each frame of real-time image and the background image to obtain a difference image corresponding to each frame of real-time image, wherein the difference image is used as a foreground image corresponding to each frame of real-time image.
According to a specific implementation manner of the embodiment of the present disclosure, the step of determining whether a moving object appears in the preset region according to the foreground image of the preset region includes:
counting the number of target pixel points belonging to the foreground object in a differential image corresponding to each frame of real-time image;
determining the total number of target pixel points in a differential image corresponding to continuous multi-frame real-time images, wherein the number of the target pixel points is greater than or equal to the total number of image frames of a first preset number;
and if the total number of the image frames is greater than or equal to a second preset number, determining that the mobile object exists in the preset area.
According to a specific implementation manner of the embodiment of the present disclosure, the step of using a first frame image of the continuous multi-frame real-time images as a background image of the preset area includes:
taking the gray scale image of the first frame image as a background image of the preset area;
the step of performing a difference operation on each frame of real-time image and the background image comprises:
and carrying out difference operation on the gray-scale image of each frame of real-time image and the background image.
According to a specific implementation manner of the embodiment of the present disclosure, after the step of determining whether the preset region has a moving object according to the foreground image of the preset region, the method further includes:
and weighting and summing the current background image and the current frame real-time image every a third preset number of frames of real-time images to obtain a new background image.
In a second aspect, an embodiment of the present disclosure provides a face recognition apparatus, including:
the first acquisition module is used for acquiring image information of a preset area;
the detection module is used for detecting whether a moving object appears in the preset area or not by utilizing a movement detection algorithm according to the image information;
the identification module is used for identifying whether a human face exists in the preset area or not if the mobile object in the preset area is detected;
and the second acquisition module is used for acquiring the face image of the preset area if the face exists in the preset area.
In a third aspect, an embodiment of the present disclosure further provides an electronic device, where the electronic device includes:
at least one processor; and the number of the first and second groups,
a memory communicatively coupled to the at least one processor; wherein the content of the first and second substances,
the memory stores instructions executable by the at least one processor, the instructions being executable by the at least one processor to enable the at least one processor to perform the face recognition method of the first aspect or any implementation manner of the first aspect.
In a fourth aspect, the disclosed embodiments also provide a non-transitory computer-readable storage medium storing computer instructions for causing a computer to execute the face recognition method in the first aspect or any implementation manner of the first aspect.
In a fifth aspect, the disclosed embodiments also provide a computer program product, the computer program product comprising a computer program stored on a non-transitory computer-readable storage medium, the computer program comprising program instructions that, when executed by a computer, cause the computer to perform the face recognition method in the foregoing first aspect or any implementation manner of the first aspect.
The face recognition scheme in the embodiment of the disclosure includes: collecting image information of a preset area; detecting whether a moving object appears in the preset area or not by using a movement detection algorithm according to the image information; if the mobile object is detected to appear in the preset area, identifying whether the face exists in the preset area or not; and if the human face exists in the preset area, acquiring a human face image of the preset area. Through the scheme disclosed by the invention, the passing speed of the user using the face recognition terminal equipment can be effectively increased or the snapshot rate of the face snapshot equipment can be increased.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present disclosure, the drawings needed to be used in the embodiments will be briefly described below, and it is apparent that the drawings in the following description are only some embodiments of the present disclosure, and it is obvious for those skilled in the art that other drawings can be obtained according to the drawings without creative efforts.
Fig. 1 is a schematic flow chart of a face recognition method according to an embodiment of the present disclosure;
fig. 2 is a schematic partial flow chart of another face recognition method according to an embodiment of the present disclosure;
fig. 3 is a schematic partial flow chart of another face recognition method according to an embodiment of the present disclosure;
fig. 4 is a schematic structural diagram of another face recognition apparatus provided in the embodiment of the present disclosure;
fig. 5 is a schematic view of an electronic device according to an embodiment of the present disclosure.
Detailed Description
The embodiments of the present disclosure are described in detail below with reference to the accompanying drawings.
The embodiments of the present disclosure are described below with specific examples, and other advantages and effects of the present disclosure will be readily apparent to those skilled in the art from the disclosure in the specification. It is to be understood that the described embodiments are merely illustrative of some, and not restrictive, of the embodiments of the disclosure. The disclosure may be embodied or carried out in various other specific embodiments, and various modifications and changes may be made in the details within the description without departing from the spirit of the disclosure. It is to be noted that the features in the following embodiments and examples may be combined with each other without conflict. All other embodiments, which can be derived by a person skilled in the art from the embodiments disclosed herein without making any creative effort, shall fall within the protection scope of the present disclosure.
It is noted that various aspects of the embodiments are described below within the scope of the appended claims. It should be apparent that the aspects described herein may be embodied in a wide variety of forms and that any specific structure and/or function described herein is merely illustrative. Based on the disclosure, one skilled in the art should appreciate that one aspect described herein may be implemented independently of any other aspects and that two or more of these aspects may be combined in various ways. For example, an apparatus may be implemented and/or a method practiced using any number of the aspects set forth herein. Additionally, such an apparatus may be implemented and/or such a method may be practiced using other structure and/or functionality in addition to one or more of the aspects set forth herein.
It should be noted that the drawings provided in the following embodiments are only for illustrating the basic idea of the present disclosure, and the drawings only show the components related to the present disclosure rather than the number, shape and size of the components in actual implementation, and the type, amount and ratio of the components in actual implementation may be changed arbitrarily, and the layout of the components may be more complicated.
In addition, in the following description, specific details are provided to facilitate a thorough understanding of the examples. However, it will be understood by those skilled in the art that the aspects may be practiced without these specific details.
The embodiment of the disclosure provides a face recognition method. The face recognition method provided by the embodiment can be executed by a computing device, the computing device can be implemented as software, or implemented as a combination of software and hardware, and the computing device can be integrally arranged in a server, a terminal device and the like.
Referring to fig. 1, a face recognition method provided in the embodiment of the present disclosure includes:
s101, collecting image information of a preset area;
the face recognition method provided by the embodiment is applied to face recognition terminal equipment in scenes such as gate machines and security check. The applied face recognition terminal equipment generally comprises a camera, a processor, a controller and other related supporting components, wherein the camera generally faces a preset area and is used for acquiring image information of the preset area, the acquired image information is sent to the processor for analysis and processing, and then the controller executes related control actions such as opening a gate, giving an alarm and the like according to an analysis and processing result.
In specific implementation, the image information of the preset area is collected through the camera. The real-time image of the preset area can be acquired in real time through the camera, and the acquired image is processed in real time or periodically. In the embodiment, continuous multi-frame real-time images are preferably acquired and then sequentially processed.
S102, detecting whether a moving object appears in the preset area or not by using a movement detection algorithm according to the image information;
after the image information of the preset area is collected according to the steps, whether a moving object appears in the preset area or not is detected according to the partial image information and a preset movement detection algorithm, namely whether a person or other articles dynamically appear or pass through the preset area or not is judged.
S103, if the mobile object in the preset area is detected, identifying whether the face exists in the preset area or not;
and S104, if the human face exists in the preset area, acquiring a human face image of the preset area.
In the above steps, if it is detected that a moving object appears in the preset area, it indicates that there may be a person or other object appearing in the preset area, and at this time, a face recognition algorithm may be started to recognize whether a face exists in the preset area. And if the human face exists, acquiring a human face image of the preset area, and performing human face recognition operation.
According to a specific implementation manner of the embodiment of the present disclosure, as shown in fig. 2, the detection step for the moving object in the embodiment is further defined. Specifically, the step of detecting whether a moving object appears in the preset area by using a motion detection algorithm according to the image information in step S102 may include:
s201, acquiring a background image of the preset area;
when detecting whether a moving object appears in a preset area by using image information of the preset area, a background image of the preset area is determined. The background image may be an image which is stored in advance or acquired in real time and corresponds to a state where no moving object appears in the preset area. The background image may be kept constant all the time or may be periodically updated.
S202, extracting a background image of the preset area from the image information of the preset area by using a background extraction algorithm to obtain a foreground image of the preset area;
after the image information of the preset area is collected, the foreground image corresponding to the preset area can be extracted according to the background image of the preset area obtained in the step.
Optionally, the background extraction algorithm may include: background subtraction method, ViBe algorithm or ViBe + algorithm.
S203, judging whether the preset area has a moving object or not according to the foreground image of the preset area.
The feature points corresponding to the background image are usually kept unchanged, and after the foreground image of the preset area is extracted according to the steps, whether the preset area has a moving object or not can be judged only according to the foreground image of the preset area.
In specific implementation, as shown in fig. 3, the image information of the preset region includes continuous multi-frame real-time images, and the background extraction algorithm is a background subtraction method;
the step S201 of obtaining the background image of the preset area may include:
s301, taking a first frame image in the continuous multi-frame real-time images as a background image of the preset area;
in a specific implementation, in order to reduce a data processing amount and improve a comparison effect, the step of using a first frame image of the continuous multi-frame real-time images as a background image of the preset area may include:
taking the gray scale image of the first frame image as a background image of the preset area;
the step of extracting the background image of the preset area from the image information of the preset area by using the background extraction algorithm to obtain the foreground image of the preset area in the step S202 may include:
and S302, carrying out difference operation on each frame of real-time image and the background image to obtain a difference image corresponding to each frame of real-time image, wherein the difference image is used as a foreground image corresponding to each frame of real-time image.
Correspondingly, the step of performing a difference operation on each frame of real-time image and the background image may include:
and carrying out difference operation on the gray-scale image of each frame of real-time image and the background image.
And, the step of determining whether the preset region has a moving object according to the foreground image of the preset region in the step S203 may include:
s303, counting the number of target pixel points belonging to the foreground object in the differential image corresponding to each frame of real-time image;
data statistics can be directly carried out, or an array is maintained in advance and used for storing the number of target pixel points which are possibly objects in the foreground image in a differential image obtained by the image of each frame in the previous N frames and the background image.
S304, determining the total number of the target pixel points in the differential image corresponding to the continuous multi-frame real-time image, wherein the number of the target pixel points is greater than or equal to the first preset number of the image frames;
s305, if the total number of the image frames is larger than or equal to a second preset number, determining that a moving object exists in the preset area.
And carrying out thresholding or histogram statistics on the difference image to obtain the number of pixel points belonging to the foreground target in the difference image, and counting the pixel points into an array and updating the array. And counting the total number of the image frames of which the number of the pixel points belonging to the foreground target in the previous N frames in the array exceeds a first preset number. And if the total number of the image frames exceeds a second preset number, namely more pixel points belonging to the foreground in the multi-frame images exist, determining that the moving object passes through.
In addition, after the step of determining whether a moving object appears in the preset region according to the foreground image of the preset region, the method may further include:
and weighting and summing the current background image and the current frame real-time image every a third preset number of frames of real-time images to obtain a new background image.
The background image is updated irregularly so as to deal with the situation that the preset area vacant state possibly exists in the process of face recognition, and the accuracy of face recognition is further improved.
After the process of moving is judged, the face detection algorithm is started to carry out a subsequent recognition task or a snapshot task. If the face is detected, carrying out the processes of face tracking, living body detection and the like to carry out a face recognition task or carrying out the processes of face tracking, face quality judgment and the like to carry out a face snapshot task; if no face is detected, the mobile detection is continued, so that the passing speed of the user using the face recognition terminal equipment can be increased or the snapshot rate of the face snapshot equipment can be increased.
Corresponding to the above method embodiment, referring to fig. 4, an embodiment of the present disclosure further provides a face recognition apparatus 40, including:
a first collecting module 401, configured to collect image information of a preset area;
a detecting module 402, configured to detect whether a moving object occurs in the preset area by using a motion detection algorithm according to the image information;
an identifying module 403, configured to identify whether a face exists in the preset area if it is detected that a moving object appears in the preset area;
a second collecting module 404, configured to collect a face image in the preset area if the preset area has a face.
The apparatus shown in fig. 4 can correspondingly execute the content in the above method embodiment, and details of the part not described in detail in this embodiment refer to the content described in the above method embodiment, which is not described again here.
Referring to fig. 5, an embodiment of the present disclosure also provides an electronic device 50, including:
at least one processor; and the number of the first and second groups,
a memory communicatively coupled to the at least one processor; wherein the content of the first and second substances,
the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the face recognition method of the foregoing method embodiments.
The disclosed embodiments also provide a non-transitory computer-readable storage medium storing computer instructions for causing the computer to execute the face recognition method in the foregoing method embodiments.
The disclosed embodiments also provide a computer program product comprising a computer program stored on a non-transitory computer readable storage medium, the computer program comprising program instructions which, when executed by a computer, cause the computer to perform the face recognition method in the aforementioned method embodiments.
Referring now to FIG. 5, a schematic diagram of an electronic device 50 suitable for use in implementing embodiments of the present disclosure is shown. The electronic devices in the embodiments of the present disclosure may include, but are not limited to, mobile terminals such as mobile phones, notebook computers, digital broadcast receivers, PDAs (personal digital assistants), PADs (tablet computers), PMPs (portable multimedia players), in-vehicle terminals (e.g., car navigation terminals), and the like, and fixed terminals such as digital TVs, desktop computers, and the like. The electronic device shown in fig. 5 is only an example, and should not bring any limitation to the functions and the scope of use of the embodiments of the present disclosure.
As shown in fig. 5, electronic device 50 may include a processing means (e.g., central processing unit, graphics processor, etc.) 501 that may perform various appropriate actions and processes in accordance with a program stored in a Read Only Memory (ROM)502 or a program loaded from a storage means 508 into a Random Access Memory (RAM) 503. In the RAM 503, various programs and data necessary for the operation of the electronic apparatus 50 are also stored. The processing device 501, the ROM 502, and the RAM 503 are connected to each other through a bus 504. An input/output (I/O) interface 505 is also connected to bus 504.
Generally, the following devices may be connected to the I/O interface 505: input devices 506 including, for example, a touch screen, touch pad, keyboard, mouse, image sensor, microphone, accelerometer, gyroscope, etc.; output devices 507 including, for example, a Liquid Crystal Display (LCD), speakers, vibrators, and the like; storage devices 508 including, for example, magnetic tape, hard disk, etc.; and a communication device 509. The communication means 509 may allow the electronic device 50 to communicate with other devices wirelessly or by wire to exchange data. While the figures illustrate an electronic device 50 having various means, it is to be understood that not all illustrated means are required to be implemented or provided. More or fewer devices may alternatively be implemented or provided.
In particular, according to an embodiment of the present disclosure, the processes described above with reference to the flowcharts may be implemented as computer software programs. For example, embodiments of the present disclosure include a computer program product comprising a computer program embodied on a computer readable medium, the computer program comprising program code for performing the method illustrated in the flow chart. In such an embodiment, the computer program may be downloaded and installed from a network via the communication means 509, or installed from the storage means 508, or installed from the ROM 502. The computer program performs the above-described functions defined in the methods of the embodiments of the present disclosure when executed by the processing device 501.
It should be noted that the computer readable medium in the present disclosure can be a computer readable signal medium or a computer readable storage medium or any combination of the two. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples of the computer readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the present disclosure, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. In contrast, in the present disclosure, a computer readable signal medium may comprise a propagated data signal with computer readable program code embodied therein, either in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to: electrical wires, optical cables, RF (radio frequency), etc., or any suitable combination of the foregoing.
The computer readable medium may be embodied in the electronic device; or may exist separately without being assembled into the electronic device.
The computer readable medium carries one or more programs which, when executed by the electronic device, enable the electronic device to implement the schemes provided by the method embodiments.
Alternatively, the computer readable medium carries one or more programs, which when executed by the electronic device, enable the electronic device to implement the schemes provided by the method embodiments.
Computer program code for carrying out operations for aspects of the present disclosure may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, Smalltalk, C + +, and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet service provider).
The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
The units described in the embodiments of the present disclosure may be implemented by software or hardware. Where the name of a unit does not in some cases constitute a limitation of the unit itself, for example, the first retrieving unit may also be described as a "unit for retrieving at least two internet protocol addresses".
It should be understood that portions of the present disclosure may be implemented in hardware, software, firmware, or a combination thereof.
The above description is only for the specific embodiments of the present disclosure, but the scope of the present disclosure is not limited thereto, and any changes or substitutions that can be easily conceived by those skilled in the art within the technical scope of the present disclosure should be covered within the scope of the present disclosure. Therefore, the protection scope of the present disclosure shall be subject to the protection scope of the claims.
Claims (10)
1. A face recognition method, comprising:
collecting image information of a preset area;
detecting whether a moving object appears in the preset area or not by using a movement detection algorithm according to the image information;
if the mobile object is detected to appear in the preset area, identifying whether the face exists in the preset area or not;
and if the human face exists in the preset area, acquiring a human face image of the preset area.
2. The method according to claim 1, wherein the step of detecting whether the preset area has a moving object according to the image information by using a motion detection algorithm comprises:
acquiring a background image of the preset area;
extracting a background image of the preset area from the image information of the preset area by using a background extraction algorithm to obtain a foreground image of the preset area;
and judging whether the preset area has a moving object or not according to the foreground image of the preset area.
3. The method of claim 2, wherein the context extraction algorithm comprises: background subtraction method, ViBe algorithm or ViBe + algorithm.
4. The method according to claim 3, wherein the image information of the preset area comprises continuous multi-frame real-time images, and the background extraction algorithm is a background subtraction method;
the step of obtaining the background image of the preset area includes:
taking a first frame image in the continuous multi-frame real-time images as a background image of the preset area;
the step of extracting the background image of the preset area from the image information of the preset area by using a background extraction algorithm to obtain the foreground image of the preset area comprises the following steps:
and carrying out difference operation on each frame of real-time image and the background image to obtain a difference image corresponding to each frame of real-time image, wherein the difference image is used as a foreground image corresponding to each frame of real-time image.
5. The method according to claim 4, wherein the step of determining whether the preset area has a moving object according to the foreground image of the preset area comprises:
counting the number of target pixel points belonging to the foreground object in a differential image corresponding to each frame of real-time image;
determining the total number of target pixel points in a differential image corresponding to continuous multi-frame real-time images, wherein the number of the target pixel points is greater than or equal to the total number of image frames of a first preset number;
and if the total number of the image frames is greater than or equal to a second preset number, determining that the mobile object exists in the preset area.
6. The method according to claim 4, wherein the step of using the first frame image of the continuous multi-frame real-time images as the background image of the preset area comprises:
taking the gray scale image of the first frame image as a background image of the preset area;
the step of performing a difference operation on each frame of real-time image and the background image comprises:
and carrying out difference operation on the gray-scale image of each frame of real-time image and the background image.
7. The method according to claim 5, wherein after the step of determining whether the preset area has a moving object according to the foreground image of the preset area, the method further comprises:
and weighting and summing the current background image and the current frame real-time image every a third preset number of frames of real-time images to obtain a new background image.
8. A face recognition apparatus, comprising:
the first acquisition module is used for acquiring image information of a preset area;
the detection module is used for detecting whether a moving object appears in the preset area or not by utilizing a movement detection algorithm according to the image information;
the identification module is used for identifying whether a human face exists in the preset area or not if the mobile object in the preset area is detected;
and the second acquisition module is used for acquiring the face image of the preset area if the face exists in the preset area.
9. An electronic device, characterized in that the electronic device comprises:
at least one processor; and the number of the first and second groups,
a memory communicatively coupled to the at least one processor; wherein the content of the first and second substances,
the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the face recognition method of any one of the preceding claims 1-7.
10. A non-transitory computer-readable storage medium storing computer instructions for causing a computer to perform the face recognition method of any one of the preceding claims 1-7.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201911353509.3A CN111191556A (en) | 2019-12-25 | 2019-12-25 | Face recognition method and device and electronic equipment |
Applications Claiming Priority (1)
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